The personal account's maximum growth rate, computed

I have finished migrating the logic from my professional prop-firm research track to a dedicated personal account system. By testing across 750 trading days using Monte Carlo (MC) simulations (a method that estimates the probability of success by resampling daily returns), I found that the profit factor (PF) of 1.64 remains stable across all configurations. The core takeaway is that the complex defensive mechanisms required to pass prop-firm evaluations are actually counterproductive for personal accounts.

Performance comparison: Fixed leverage (k)

In these tests, k represents a multiplier for the base risk. I found that growth is nearly linear relative to k. While higher leverage increases returns, the primary constraint is drawdown (DD) tolerance. The probability of a 50% drawdown (P(DD>50%)) shows the risk of ruin.

k	Annual Return (Monthly)	Max DD (Median/95%)	P(DD>50%)
3	36.1% (2.60%)	20% / 33%	0.1%
5	62.7% (4.14%)	32% / 50%	4.8%
8	104% (6.14%)	47% / 69%	39.5%
10	132% (7.27%)	56% / 78%	68%
In other words, while a k of 10 offers a high annual return, the 68% probability of a 50% drawdown makes it effectively a gamble.

Why “prop-firm” tools fail on personal accounts

I tested several techniques designed for prop-firm challenges to see if they offered a “free lunch” for personal trading:

Flat-guarding (Tail cutting): In prop firms, this is essential to avoid the “cliff” of immediate disqualification at a 5% or 10% loss. On a personal account, there is no such cliff. Cutting losses at -10% simply prevents the system from recovering, effectively paying a cost for protection that isn’t needed.
Dynamic k and trailing floors: These methods attempt to adjust risk based on proximity to a limit. My tests showed annual returns of only 20 to 27%, which is roughly half to one-third of the return of a fixed k=5 strategy. These tools are strictly for games where a disqualification boundary exists.

Final verdict and implementation

The optimal approach for a personal account is simple: fixed leverage. I recommend a conservative k=3 for those prioritizing stability, or k=5 for those seeking more aggressive growth. I have now separated the codebase to keep these environments distinct:

Python Logic: scripts/systems/personal_system.py now houses the core logic. At k=3, this configuration yields a PF of 1.66 and a monthly return of 1.659% with a max DD of 19.3%.
MT5 Implementation: The new mt5/PersonalCoreV1.mq5 (v1.0.0) is live. I have stripped away the complex prop-firm defenses, leaving only a hard withdrawal line set at -35% of the initial balance. By removing unnecessary complexity, the system is now leaner and better suited for the realities of personal trading where survival is defined by capital preservation rather than passing a rigid test. Note that these models do not currently account for swap costs, which will weigh more heavily as k increases. Additionally, the -35% withdrawal line acts as a static floor that becomes effectively looser as the account grows.

How this connects

This verification builds on earlier ones (what failed before and what I tried this time, comparisons between approaches).

Code to reproduce

You can reproduce this with the following scripts (see repo).

scripts/systems/personal_system.py